Related Experiment Video
Updated: Jul 14, 2025

08:12
A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
Published on: March 1, 2022
2.5K
Measuring multi-dimensional disparity index: A case of Nepal
Prakash C Bhattarai1, Milan Shrestha2, Prakash Kumar Paudel3
1Kathmandu University-School of Education, Hattiban, Lalitpur, Nepal.
Plos One
|October 5, 2023
Summary
Nepal
Area of Science:
- Socioeconomic studies
- Regional development analysis
- Public policy evaluation
Background:
- Existing disparity assessments are often mono-dimensional.
- Nepal faces multi-form disparities across government levels.
- A comprehensive measurement tool is needed for effective policy.
Purpose of the Study:
- Introduce the Multi-dimensional Disparity Index (MDI) for Nepal.
- Develop a robust scale to measure multi-form disparities.
- Analyze disparities across Nepal's three tiers of government.
Main Methods:
- Adopted Santos and Alkire's (2011) measurement scale.
- Utilized a Semi-Delphi approach with thematic experts.
- Constructed MDI with six dimensions and 34 indicators.
Main Results:
- Nepal's overall MDI score is 0.388.
- Karnali province exhibits the highest disparity.
- Bagmati province shows the least disparity.
Conclusions:
- MDI offers a broader approach to measuring multi-dimensional disparities.
- The index provides crucial insights for policy in Nepal.
- Identified specific regional disparities for targeted interventions.
Related Concept Videos
Ordinal Level of Measurement
24.8K
The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks...
Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks...
24.8K
Skewness
11.7K
The measures of central tendency calculated from a data set may not reveal much about its intrinsic distribution. If a plot is made of the data set’s values, the mean and the median may not only differ, but also the plot may have more values on one side of the central tendencies. Such a data set is said to be skewed towards that side.
The longer the tail of the plot on one side, the more skewed it is. The skewness of a data set’s values suggests that the measures of central tendency...
The longer the tail of the plot on one side, the more skewed it is. The skewness of a data set’s values suggests that the measures of central tendency...
11.7K
Wilcoxon Signed-Ranks Test for Median of Single Population
149
The Wilcoxon signed-rank test for the median of a single population is a nonparametric test used to evaluate whether the median of a population differs from a specified value. Unlike parametric tests, it does not require data to follow a normal distribution, making it suitable for non-normal or small samples. The test begins by calculating the difference (d) between each observation and the hypothesized median. The absolute values of these differences are ranked in ascending order, with ties...
149
Interval Level of Measurement
15.3K
For effective statistical analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
Data measured using the interval scale are similar to ordinal level data because they have a definite arrangement. However, in the interval level of measurement, the differences between data values are meaningful even though the data does not have a starting point.
Temperature is measured using the interval scale. It is measurable data, and the difference between...
Data measured using the interval scale are similar to ordinal level data because they have a definite arrangement. However, in the interval level of measurement, the differences between data values are meaningful even though the data does not have a starting point.
Temperature is measured using the interval scale. It is measurable data, and the difference between...
15.3K
Variation: Normal Distribution, Range, and Standard Deviation
22.3K
In the field of psychology, there are several ways to organize measurements of a trait, feature, or characteristic (i.e., variables). Qualitative data, such as ethnicity, can be tabulated into a frequency count to provide information about the proportion, as well as the variety of groups in a sample or population. On the other hand, researchers can perform a wider set of calculations on quantitative data. The mean, mode, and median, for instance, are central tendency measures to identify a...
22.3K
Ratio Level of Measurement
18.3K
The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
A set of data measured using the ratio scale takes care of the ratio problem and provides complete information. Ratio scale data are like interval scale data, except they have a zero point and ratios can be calculated....
A set of data measured using the ratio scale takes care of the ratio problem and provides complete information. Ratio scale data are like interval scale data, except they have a zero point and ratios can be calculated....
18.3K

